ABSTRACT One of the most important aspects when transporting multiple different liquid products within the same pipeline, is being able to know where the head and tail of each batch is at any given time based on the current operation to provide an accurate Estimated Time of Arrival (ETA) at upcoming stations. With this information, pipeline operators can be ready to execute valve swings at intermediate delivery and injecting stations helping minimize product contamination. It is relatively simple to track these batches and their interfaces when the pipeline has a uniform and gradual elevation profile. However, when pipelines travel through mountainous regions with high and drastic elevation changes, the ability to track the head and tail of these batches become far more complex due to the presence of slack. When slack is present, the common assumption that the volume of liquid equals the physical volume of the pipe is no longer valid. The fraction of the pipe filled with liquid, called the "liquid holdup", has a large impact on the position of the batch head and tail. As a result, the accuracy of the volume contained within the region and the corresponding Estimated Times of Arrival at upcoming stations are directly affected. An empirical approach using volume accumulation at a pipeline injections and deliveries has been successfully implemented with an end user to account for the liquid volume within a specific region known to have slack during normal operations. However, this approach does not provide an accurate solution for the exact location of where the slack occurs, nor the size of the slack itself, which has a direct effect on the location estimate for when the head or tail is passing through the area. With the current empirical approach, Estimated and Actual Times of Arrival are within a 15-minute time window after a batch has traveled a total distance of 1,200 km (746 mile) with a drastic slack region along the route. This paper provides an analysis on the current empirical approach used in the daily operation by the existing end user, and how the results compared to a full scientific approach running a slack model based on the field instrumentation, and the physical properties of the pipeline.

ABSTRACT Upstream gas supply planning and allocation contains 3 cycles namely long term (20 years - end of life of a field) mid-term (up to 1 year) and short term (72 hours). Since the upstream assets are owned/operated by different companies under various production sharing contracts, each of the operating companies prefer to maximize their production and recover the investment costs at the earliest. A regulator acts as a custodian to ensure that all stakeholder's entitlements are protected. The custodian relies on economic and hydraulic modelling to analyse the production plateau's shared by various operating companies together with the demand profiles for viability. The commercial planning team of the custodian works closely with flow assurance engineers before confirming the production numbers as the planners are unaware of any capacity constraints in the physical network for flow. In the short term, an integrated network operator breaks the long term demand numbers and controls the network for seamless delivery of gas from upstream to LNG plants (mostly). The purpose of the paper is to highlight the challenges faced by planners and engineers during the planning cycles and to make appropriate recommendations.

ABSTRACT Oftentimes smaller transmission systems will be designed and built with only essential telemetry in mind. While deliveries are not monitored in real time on SCADA, monthly consumption data is recorded and available. While this amount of telemetry is sufficient to accurately and appropriately monitor the pipeline, it may not provide enough data to produce a hydraulically accurate simulation model. We set out to determine the feasibility of creating a Transient real time model of one such small transmission system where as much as 80% of the deliveries are not on SCADA. This ~75-mile-long system is mostly comprised of larger seasonal agricultural customers which can draw the system down and impact the few residential distribution systems that are on the mainline. The real time model can be used to analyze potential improvements and/or system expansion alternatives and their effect on pressure at the delivery border station. We combined the use of a hydraulic simulator, load prediction software, and data analysis to develop a methodology to simulate the transient behavior for these non-SCADA points. Where SCADA was not available, historical data from similar type customers was analyzed to produce profiles that could be applied. A Real Time Model (RTM) was built utilizing both actual SCADA data and simulated SCADA to accurately model the transmission system. This model demonstrates that despite a large gap in the available real-time SCADA data, where missing data could account for as much as 80% of the total load on the system, we can model the behavior of the system by calculating and accurately estimating flows and pressures. In addition, users can easily convert the RTM into a transient predictive model where further feasibility and system improvements can be analyzed.

ABSTRACT Sand management technology has become more prevalent in the petroleum industry to increase well production. Sand may deposit on pipeline walls, causing problems such as pipe blockage, reduced flow area, structural pipe issues, abrasion, corrosion, and low production in wells. This paper explores the multiphase model and computation algorithms used to simulate multiphase flow with sand particles through a subsea pipeline to predict the pressure gradient, transport velocity, and sand deposition. Being able to predict sand accumulation and understanding real-time sand velocity in a pipeline can help define design criteria for subsea pipelines and help pipeline operators maximize production while minimizing well and pipeline downtime. INTRODUCTION Sandstone reservoirs are the source for most of the world's hydrocarbons; however, sand is a common by-product of oil and gas production, especially when producing from reservoirs with low formation strength. When rock around the well perforations is weak, the reservoir fluids can push sand or solid material into the wellbore. Sand in the produced oil and gas enters the pipeline network, which can increase frictional pressure loss, pipeline damage due to erosion, potential equipment failure, and sand deposition (causing flow assurance problems and pressure changes). The traditional sand management method involves preliminary sand extraction from the produced fluid before it is released into the main pipeline. Unfortunately, this method is expensive and not applicable in all cases, such as deep, subsea pipelines. As a result, newer sand management methods focus on tracking the amount of sand in the pipeline and operating the pipeline at conditions that minimize the risks. With these new sand management methods, pipeline simulations become an even more powerful tool for pipeline operators to identify the influence sand has on pressure and temperature changes in the pipeline, detecting erosion and sand deposition, and understanding the impact different operating conditions have on the pipeline performance and safety. This paper discusses a set of sand management modeling and simulation algorithms and approach to detect sand deposition and erosional velocity. The approach was applied to a cluster of offshore platforms and wells connected by a subsea pipeline; in the case described, these simulated sand deposition and erosional velocity events were compared to real-time pipeline data—including theoretical and actual pipeline pressure loss—and verified, allowing the pipeline operator to take appropriate mitigation actions and reduce lost production opportunity.

ABSTRACT In recent years, pipeline operators have faced reduced production environments caused by declining brownfield operations and capital constraints induced by oil prices, among other factors, which have led to pipelines operating well under their designed capacity and challenges such as congealing—the precipitation of wax solids in a crude oil pipeline. This paper discusses how models are built using scientific principles and how simulation may be used to predict where congealing is or may occur inside a pipeline. Finally, a case study from a major oil and gas company's site demonstrates how these modeling and simulation techniques may be effectively applied in the field. INTRODUCTION AND BACKGROUND Pipeline operators are currently challenged with operating pipelines safely in reduced production environments, which have been caused by declining brownfield operations, capital constraints brought on by oil prices, and the lack of drilling rigs to keep pipelines full. These present conditions result in pipelines operating well under their designed capacity and challenges such as congealing. Congealing refers to the precipitation and nucleation of wax solids in a crude oil pipeline. It is initiated by a temperature gradient between the pipe wall and the centerline flow, leading to high-yield flow stress and causing changes in flow behavior. This paper discusses the physical considerations that contribute and are necessary to detect congealing followed by a series of modeling steps to accurately simulate when and where congealing occurs in a pipeline while accounting for multiphase flow of differing compositions from multiple producers. In turn, this information can automatically be displayed as a visual pipeline profile, allowing operators to understand their entire pipeline operation from remote locations and view critical parameters and events, such as congealing, leak detection, and slugging. These modeling and congealing algorithms were implemented and validated at a major oil and gas company's site on a 150-km (~93.2 mi) commercial pipeline network used to transport roughly 50,000 BOPD (7,949 m 3 /day) from 11 gathering stations to a distribution tank farm. The main transportation pipeline was designed to transport 500,000 BOPD (79,490 m3/day). Congealing events were detected and verified by comparing the simulated and assayed pipeline data. Prediction time averaged between three and six hours in advance of the congealing event, allowing the pipeline operator take appropriate mitigation actions and reduce lost production opportunity (LPO).

ABSTRACT Testing of pipeline leak detection systems can be challenging. It is also a critical activity which provides key information on the systems capability for communications to regulators and key stakeholders. The authors describe an API RP 1130 compliant test method that relies on the development of a limited number of realistic "leak signatures" that are superimposed on archived SCADA data in a way that preserves not only a faithful representation of the leak, but the real-world impacts of noise, calculation uncertainties, and measurement errors as well. In addition to maintaining high hydraulic fidelity, coverage and flexibility, this procedure is performed at low cost while potentially providing a greater degree of insight into the detailed performance of the leak detection system than can be achieved with other methods. INTRODUCTION AND BACKGROUND The Need for Testing of Pipeline Leak Detection Systems A leak detection system (LDS) is a safety and integrity-critical component of an operating pipeline that is designed to help mitigate negative consequences following an unplanned commodity release. Its intended purpose is to reduce the potential negative impacts from a breach in pipeline hydraulic integrity (e.g., a leak with its resulting spill). Reducing these potential negative impacts is achieved by rapidly detecting the leak and determining its most probable location. Determination of these factors in as short as time frame as possible provides key information that is critical in terms of enabling the pipeline operator to respond faster, more effectively, and with greater precision. Note that the most commonly applied method for leak detection is via Computational Pipeline Monitoring (CPM) systems, which are the explicit focus of this document. As part of the operator's overall spill response plan the organization should be able to quantify the leak detection system's predicted performance. This allows the operator to identify areas where further leak detection improvements are desirable and refine location specific response plans. It also provides a mechanism by which the LDS performance can be monitored and tracked over time. Quantifying the leak detection performance requires testing. As stated in the American Petroleum Institute recommended practice 1130 (API 1130), "[t]he primary purpose of testing [quantifying] is to assure that the CPM system will alarm if a commodity release occurs." Note that while API 1130 is specific to Computational Pipeline Monitoring leak detection systems, the quantification of system testing is applicable to all leak detection systems.

Abstract This paper reviews the physical and practical considerations that need to be addressed to develop an accurate and robust computational model of the transportation of multiphase fluids across large-scale pipelines. It then demonstrates the accuracy of the Real-Time Simulation System , which was designed according to the scientific principles that are laid out in the paper. To demonstrate the accuracy of the model, computed pressures, temperatures, and mass flow rates along a commercial pipeline are compared against experimentally measured values. Introduction Pipelines in oil and gas production systems normally transport multiphase mixtures of oil, water, and gas. Simulation of complex multiphase flow processes is an important aspect of efficient oil field operation. Safety and optimization rely on a detailed understanding of multiphase flow behavior. 1 The multiphase flow model that is built into the simulation software employs conservation laws and well-established empirical formulas to simulate the changes that occur to the mass flow rate and thermodynamic properties (pressure, temperature, etc. ) of single or multiphase fluids that are transported across industrial scale pipelines. 2,3 A diverse set of equations of state are accessed by the model to simulate a wide variety of materials and to ensure that the model can handle the difficulties that arise from fluid compression and phase transitions. 4,5,6 When modeling the transportation of water/steam mixtures (that do not include contributions from oils or other gases), the multiphase flow model also determines the change that will occur to the quality of the steam ( i.e. the composition of the water/steam mixture). Scientific Foundation Multiphase flow processes involve a combination of materials having different properties and often exhibit relative motion among the phases. 1,2 The multiphase flow model is designed to predict the fluid properties, mass flow rate ? , pressure P , and temperature T of a fluid at different distances along the pipeline x and at different moments in time t . In order to make those predictions, the initial mass flow rate and composition (relative amounts of oil, water, and gas) of the fluid must be specified. Values of the key physical properties (density, viscosity, etc. ) of the fluid must also be identified either by using empirical formulas 4-6 to calculate those values or by specifying them as input parameters. Once the necessary input parameters have been specified several mathematical algorithms work in consort to determine the changes to ? , P , and T . The specific algorithms that are used at a given point of the pipeline are chosen to account for the dominant forces that effect the properties of the fluid at that point.

Abstract This paper examines the feasibility of Real Time Transient Model (RTTM) based methods for gas pipeline leak detection, elucidates the factors that must be managed for effective gas pipeline leak detection, and examines factors that impact leak detection and location sensitivity. Introduction A growing regulatory focus on minimizing the impacts of ruptures in natural gas commodity pipelines is increasing the pressure on the operators of such systems to provide means of rapidly detecting and locating such leaks. Leak detection systems have become standardized components of liquid commodity pipelines over the last few decades, but have not been emphasized for natural gas systems. Although many methods have been used to detect leaks in liquid systems, the most commonly used approach uses real time transient models and a mass-balance approach to detect commodity losses. The approach is extensible to gas systems in a fairly straightforward manner, and this paper will discuss such implementation. However, it is worth nothing that gas systems have certain differences that make them distinct from liquid pipeline systems. One difference is that gas pipelines, especially if they are part of or support gas distribution, have the potential to be far more highly networked, branched and looped than liquid transportation systems. Gas is a far more highly compressible commodity than most liquids are, and this has ramification for desired levels of instrumentation and speed of response. Finally, gas pipelines are more highly typified by maintenance requirements that can interfere with or degrade the performance of RTTM systems. Another significant different between liquid and gas pipeline leak detection requirements is that generally, in a liquid line, a very large leak may be quickly identified by rate of change alarms. In contrast, a large leak in a gas pipeline, because of the compressibility of the gas, will cause much slower changes in the pipeline pressure. A gas pipeline therefore, may need to rely on an RTTM based leak detection system even for the reliable and timely detection of very large leaks. This paper attempts to illuminate these issues and equip the reader to understand and deal with them.

ABSTRACT For Saudi Aramco, keeping the nation's oil fields in optimal condition is an operational requirement. Strategic water injection is essential for long-term, maximum oil recovery. Keeping a steady supply of treated seawater flowing into an oil field reservoir through more than 600 wells is a very challenging task. We have to maintain the water pressure, quantity and quality. If the water quality specifications are not met, then it could have a negative impact on the piping integrity and the reservoir. The use of seawater means that we are able to preserve the nation's natural water resources for use by future generations. To achieve the objective of proper reservoir support, in this presentation we will focus on utilizing a new technology in our operations, which is a great enabler of safer, more efficient, more reliable, and more profitable operations. INTRODUCTION It is a common understanding that your body needs water intake to stay fit and healthy; try going without drinking water for a while, and you'll see just why. What is less known is that the Kingdom's vast oil reservoirs also need water intake to prolong their longevity. In their own unique way, they too rely on water for optimal performance. For Saudi Aramco, keeping the nation's oil fields in optimal condition is not simply an option - it is a must. Without water injection, oil production levels cannot be maintained and could be significantly impacted and drop. Although oil production would not immediately stop without water injection, the health of the oil field would be severely affected, causing a decline in the oil it produces over time. Injected seawater replaces the oil that is extracted from the reservoir. This offsets the pressure decrease in the field that is caused by oil production. It is this decrease in pressure that affects how much oil the reservoir can produce.

ABSTRACT: This paper presents a method for assessing the leak detection performance of commercial real-time pipeline monitoring software. The method has two key advantages: (1) it is applicable to all types of leak detection software that accept ASCII input data, and (2) no prior knowledge of the software calculation method is required. Real Time Transient Model (RTTM) performance has been assessed for the Statoil-operated Troll oil pipeline (TOR1). Leak scenario boundary data sets (pressure, flow and temperature) are calculated by transient simulation of leaks using production data as input. This was accomplished using an Olga pipeline model tuned against production data. RTTM simulations indicate that for the TOR1 system with current leak detection thresholds, leaks representing approximately 5 % of the pipeline flow rate are detectable within about two hours of the leak onset. A theoretical assessment based on the API publication 1149 indicates that leaks of this size should be detectable within about 15 minutes. The approach outlined in this paper enables Statoil to carry out targeted alterations to improve the leak detection performance of these software systems. INTRODUCTION AND BACKGROUND Liquid transport pipelines on the Norwegian Continental Shelf (NCS) show excellent performance. In the last decade, approximately 740 miles of pipelines conveyed an estimated 900 Mbbl of liquid hydrocarbons [1]. In the same period, a single leak event caused a total leakage of 777 bbl of condensate [2]. The reasons for this pipeline performance include robust design, and careful operation and maintenance. Nevertheless, pipeline leaks and ruptures can occur, for several reasons [3]: Pipeline corrosion and wear; Operation outside design limits; Unintentional third party damage; Intentional damage. Analogous leak events in the (much larger) gas transportation system include the 2004 Jotun gas export pipeline rupture [4] and the 2008 Kvitebjørn gas export pipeline leak [5]. Both of these incidents were preceded by large mechanical stresses on the pipelines, caused by unintentional third party interference. These leak causes are also relevant to liquid pipelines. With respect to health, safety, the environment and economics, the purpose of leak detection is to reduce the consequences of the leak. Full pipeline rupture will, with few exceptions, be discovered by control room operators within a short time, through abnormal declining pressures or flow rates. However, sizeable leaks can give only small sensor deviations and thus pass undetected unless sensitive, dedicated leak detection systems are installed. Time-continuous methods covering entire pipelines include simple or complex mass balance (inventory tracking) methods, acoustic detection of leaks, plus other forms of distributed sensing such as oil permeable tubes. As with all leak detection methods, the goal is to detect the leak-causing event and the resulting fluid emanating from the pipeline. These technologies require: Coverage of the entire pipeline length; Time-continuous coverage; A robust and unambiguous correlation between the leak and the measured quantity (loss of mass, acoustic signal, detected hydrocarbon), and; A means of communication and evaluation between the sensor and operational personnel.

ABSTRACT This paper describes in detail the key experiences of a well-established Oil & Gas company in Latin America related to the implementation and evolution of a Pipeline Advanced Application project; how these applications have helped the organization to improve the knowledge of its own networks, and how they have provided a solid foundation to manage the critical problem of product theft. Ecopetrol S.A. (Ecopetrol) is responsible to build and operate the whole Colombian transport infrastructure and distribution of oil & gas and refined products by means of its 8,500 kilometer network of pipelines which run from the production centers to the refineries and ports in the Atlantic and Pacific oceans. Ecopetrol has the responsibility to guarantee supplies of oil and biofuels production throughout Colombia, whether its own production or through domestic or foreign third party providers (Figure 1). Ecopetrol started implementing real-time online application technology in 1998, mainly motivated by the desire to eliminate hydrocarbon leaks, thefts and losses occurred in the provision of the transport service. The paper is supported by field data gathered by Ecopetrol that describes the evolution and performance of the application as well as the overall performance achieved. COMPANY DESCRIPTION The pipeline network of Ecopetrol consists of 50 transportation systems, including more than 52 supply, delivery, storage and pump stations. The transportation network is grouped into two main systems: multiproduct pipelines and crude pipelines. Due to the complex topography of Colombia, including the Andes mountain chain located at the central and west side of the country, almost all of these pipelines have elevation profiles with dramatic variations from 0 meters to 3,000 meters (0 to 10,000 feet) and temperature changes of up to 30° C (54° F) within a few miles Technology Background Ecopetrol controls and operates all its multiproduct pipelines through a SCADA system located at the Main Control Center in Bogota. On top of the SCADA system Ecopetrol implemented a set of advanced applications. These applications are based on a real time transient model, which consists of a hydraulic and thermodynamic representation of the product's physical behavior while traveling through the pipelines. The model takes into consideration heat exchange with the surrounding environment, the physical properties of the pipeline and the physical properties of the transported products. The model thoroughly details the pipeline's present state under any operating scenario. Using the real time model as a platform for Ecopetrol's multiproduct pipelines the following applications have been configured: Leak Detection & Location, Shut-In Leak Detection, Batch Tracking, Scraper Tracking, and an Operator Trainer tool. Currently Ecopetrol has all of its 14 multiproduct pipelines configured and running with applications for Leak Detection, Batch Tracking and Scraper Tracking.

ABSTRACT The call came in at 9pm UK time. Our site engineer reported that the live leak test was going ahead. On a frosty night in January, I drove to the office in Stockton, to meet up with the rest of the team. Across the globe, in a warmer and more humid climate, a team from Oil Search in Papua New Guinea were preparing to remove product from an oil pipeline to establish the viability of the latest technology in which they had recently invested. This paper describes a shared experience: the successful implementation of a model based solution for leak detection using a new liquid model, a team spread out over four continents and how a simulated pump was used to reduce false alarming across an open valve with an abnormal pressure lift! The team had been working for several weeks to commission the leak detection system and had faced a fist-full of problems. ESI's creative engineers worked with Oil Search and produced a flexible model based solution that overcame problems with data outages, spiking pressure measurements and other abnormal measurements. Now all of that effort would be tested. Oil Search's previous Rupture Detection System used two methods: Comparing differences in calculated mass of oil into and out of the pipeline, allowing for packing, in 30 second time frames. A differential flow alarm if the line pressure fell and the differential rate of flow was greater than 2,000 BPD Oil Search performed a leak test on this system in August 1994 with satisfactory results. However, it was accepted that during normal operations of start-up and shutdown, false alarms were experienced. This paper addresses: Benefits of a model based leak detection system Flexibility of using a model based leak detection system How advanced analysis tools can identify optimum leak detection sensitivity for all operations Procedures for performing a live leak test Problems overcome during the project implementation The benefits and pitfalls of a globally diverse team BACKGROUND Oil Search Limited (OSL) is an oil and gas exploration and development company that have been operating in Papua New Guinea (PNG) since 1929. It is PNG's largest oil and gas producer, and operates all of PNG's producing oil and gas fields. In 2006, Oil Search was responsible for generating 16% of PNG's gross domestic product and 22% of its export revenue. As PNG's largest oil and gas producer, Oil Search moves over 16 million barrels per year through 168 miles (270 km) of pipelines between its Central and Gobe processing facilities and its Kumul Marine Terminal, where product is loaded onto ships. Crude oil is periodically moved in 650,000 barrel batches (103,350 m3)

ABSTRACT The purpose of this paper is to show how a pipeline company can integrate its operational and commercial practices into a real-time environment that will allow safe, efficient, and profitable operations. Operational pipeline modeling & management, SCADA, and commercial transaction systems can be combined to provide hydraulic validations of business transactions and, resultantly, provide a real-time and forward look at pipeline expectations. This helps pipeline companies better manage oil and gas shipments on a real-time basis and to comply with issues of restructuring and regulations to avoid unnecessary costs and build revenue. Transpetro in Brazil has automated and integrated many of its processes. This paper will define the issues encountered by Transpetro and the steps it took to integrate both its operational and commercial business systems into a real-time environment. The paper will also document the integration of systems to merge the commercial business transactions and operational parameters to provide forward looking models necessary to utilize the entire pipeline system effectively. The solutions developed by Transpetro could be applied to many other pipeline companies. About Transpetro Transpetro is a full subsidiary of Petroleo Brasileiro S.A. - Petrobras and was incorporated on June 12, 1998. Its mission is bulk transport and storage of petroleum and its byproducts and of natural gas through pipelines and ships, and to operate terminals. There are two big networks (Northeast and Southeast), each one with a number of pipelines: The Northeast Network runs along seven states in Brazil (Bahia, Sergipe, Alagoas, Pernambuco, ParaÍba, Rio Grande do Norte e Ceará) and moves approximately 9 Million m 3 /day. The entire network includes three (3) compressor stations. This network is composed mainly of five pipelines: GASFOR, NORDESTÃO, GASALP, GASEB, and a Sub-Network. The Southeast Network runs along three states (Rio de Janeiro, São Paulo e Minas Gerais) and moves 20 Million m 3 /day. The entire network includes five (5) compressor stations and it has the following pipelines: GASBEL, GASVOL, GASPAL, GASAN, Merluza, GASDUC I, GASDUC II, and G1, G2, G4, Namoradao, Enchovao (G3), GASCAB I (G5) and GASCAB II. The last seven are essentially gas gathering lines that bring gas from offshore. Among other business TRANSPETRO sells gas transportation capacity to a number of companies interested in moving gas from the producing site to the consumption points. TRANSPETRO's client companies are called "shippers" who request on a daily and monthly basis certain amount of gas to be transported by TRANSPETRO from a supply point to a given delivery point. TRANSPETRO also provides operational, maintenance, and administration services to other transporters. TRANSPETRO strive to maximize the amount of transported volume while maintaining the operating limits of the pipeline. Transpetro System The Transpetro system consists of a pipeline hydraulic simulator with both real-time and predictive models, and a nominations system. Operations use the real-time model to monitor the state of the pipeline networks for purposes of operational analysis, linepack/pressure management, etc.

ABSTRACT The temperature of the medium surrounding a pipeline significantly affects the pipeline's hydraulic capacity. However, often the ambient temperatures are approximated by statistical averages of historical data, hard-coded in a model file. Such data may at times deviate from the true temperatures by more than five degrees Fahrenheit. Especially for on-line systems the lack of up-to-date ambient temperature data may limit maximum utilization of the existing pipeline capacity. Integration of up-to-date ambient temperatures will therefore enable Gassco, and other pipeline operators, to improve the usage of the available network capacity and allow for better planning of the day-to-day capacity that can be offered for sale. This paper presents how up-to-date sea bottom temperatures were integrated in Gassco's Pipeline Modeling System. The increased modeling accuracy enables Gassco to commit approximately an additional 250 million SCF/d gas for any particular cold day. THE IMPORTANCE OF UP-TO-DATE AMBIENT TEMPERATURE DATA Gassco supplies Norwegian gas to the European market through more than 4 850 miles (7 800 km) of large diameter high-pressure sub-sea pipelines. Contractual deliveries in 2005 amounted to nearly 3 000 billion SCF (84 billion Sm3). During winter, the request for gas exceeds the current estimated transport capacity of the pipelines. Consequently, Gassco constantly evaluates the accuracy of the margins applied when calculating the hydraulic capacity of the pipelines. Such studies concern in-situ capacity tests of the pipelines, evaluation of the theoretical aspects of flow models (such as the friction factor used in the pipeline models, see Langelandsvik et al. , 2005), and improvement of data sources that are used as input in the pipeline models. Currently, capacity estimates are typically based on traditional on-line data from the transport network (pipeline inlet/outlet pressure, flow rates, gas temperature and composition) in combination with conservative estimates of the historical ambient temperatures. A preliminary study showed that when actual day-to-day ambient temperatures were integrated into the Pipeline Modeling System (PMS), Gassco would be able to more accurately predict and use the available transport capacity in its gas pipeline system. For example, Figure 1 shows the hydraulic capacity that is offered for sale (green line) for a particular pipeline. This capacity is an estimate based on a conservative scenario, i.e. , high ambient temperatures based on statistical historical data (red line) combined with an additional margin. However, in case up-to-date temperature data shows that the ambient temperature in fact is lower, the extra margin in the pipeline capacity can be utilized. In this example, nearly 3% extra gas can be transported and sold on a cold day. Improved accuracy in the ambient temperature data thus makes it possible to offer an increased pipeline capacity and thus to better meet the increased demand for gas during the winter season. For instance, for each particular cold winter day, the increased modeling accuracy makes it possible for Gassco to commit approximately 250 million SCF gas per day extra.

ABSTRACT Traditionally, pipe flow models have been derived from engineering data (such as pipe and fluid properties) by constructing the appropriate nonlinear partial differential equations [1]. This engineering data comes from a variety of sources and is often wrong. Therefore it has been necessary to tune these models, either manually or automatically, until their results matched the real-world behavior of the pipeline. However, with the aid of some usually-valid assumptions about the underlying equations, it is possible to construct a transient pipe model solely from historical SCADA data, thus eliminating the need to find, input, or validate pipe or fluid property information. This paper presents a method for automatically generating such models, studies the accuracy of the generated models for a real gas pipeline, and examines some possible applications. 1. INTRODUCTION Online models are one of the most useful applications made by the pipeline simulation industry. They have many different functions including detection of leaks and other anomalies like failing equipment, describing what is happening in the line at unintsrumented locations, and maintaining an accurate picture of the current state of a pipeline for use in launching lookahead models. Look-ahead models, which are close relatives of online models in that they depend on SCADA data to give them their initial state, can determine feasibility of planned operations, survival times, and ETAs of important events. However, creating an accurate online model can be difficult. Even assuming that the underlying model engine is correct and bug-free, configuring these programs depends on getting an accurate description of the physical properties and layout of the pipeline itself, the properties of the fluid being pumped, and numerous other numbers that must be drawn from the real world. There is plenty of opportunity for human error while entering this data into the model; in addition, much of this information may not have been used for ages, so the pipeline operator would not necessarily know if it was still accurate. On top of this, the properties of pipelines change over time. This necessitates some sort of automatic adjustment of the original properties, which is typically accomplished by "tuning" pipe roughnesses, fluid properties, ground thermal conductivity, and the like. This is especially necessary in the case of an application like leak detection that requires high model accuracy. This sounds like a lot of work, and it is. However, there's an alternative to building a model starting from a physical description of the pipeline: you can instead start from the observed behavior of the pipeline. If a program can accuately predict what some of the SCADA instrumentation will read given values for some of the other SCADA points (e.g. predict the flows if it knows the pressures, or vice versa) then it will effectively be a model, capable of fulfilling a subset of the online and look-ahead model applications described above.

ABSTRACT Real-time models and associated applications have been widely used to support the safe and efficient operation of pipelines from within the confines of the pipeline operations environment. Commercial systems have also been independently implemented to manage the business relationships between gas suppliers, shippers, transporters, and end users; however, the direct interchange of information between models and commercial business systems has typically been limited. As part of a comprehensive upgrade of their gas shipping system, Petrobras has implemented a real-time model on several of their pipelines, integrating SCADA and model data with the new shipper system. The shipper system provides Petrobras with the capability to schedule, consolidate, allocate, and provide detailed energy and volume information for invoice generation. Real-time model and SCADA data are used by the shipper system to provide real-time supervision of the shipper contracts by monitoring and reporting contractual gas quality, volume, and operational pressures, directly against commercial contract parameters, in real time. Further, a nomination forecasting application is used to forecast supply and demand, identifying future volume and energy penalty conditions. Through web access, each client also has the capability to monitor real time flow profiles against their nomination and nomination forecast profiles, allowing the client to be proactive in avoiding penalties. In this paper, an overview of the shipper system functionality and its integration and use of real time data will be provided. The challenges, experiences, benefits, and future enhancement considerations will also be discussed. INTRODUCTION The Brazilian gas market is regulated by ANP (Petroleum National Agency) from its production to the delivery to distributors. Distribution to final consumer is a monopoly of each Brazilian State government which is executed through concession to private companies. A Federal Law from 1997 defines six different roles for the gas market and the activities and combinations allowed among them. These roles are: producer, processor, importer, shipper, transporter and distributor. The diagram in Figure 1 below shows the relationship between these roles with respect to the physical flow of gas and commercial relationships. It should be noted that the processor is not shown in this diagram. In reality the processor sits between the transporter and the producer. The retailer in this diagram is known as the shipper throughout this paper. Prior to 1997, Petrobras, a corporation formed by the Brazilian government in 1953, was the only player in the Brazilian gas market, except for the distributor role that was already given to the States by the constitution of 1988. After the 1997 Federal Law, Petrobras created Transpetro to act as transporter, operating all existing pipelines in Brazil. At the same time, a new private company was created to build the Bolivia-Brazil pipeline, with 51% participation of Petrobras. In the year 2000, a natural gas business unit was created in Petrobras to play the shipper role. As the largest oil & gas company in Brazil, Petrobras is the main shipper for both gas transportation companies.

ABSTRACT The aim of the paper is to inform on verification, advantages and limitations of the real time systems installed at the dispatcher center of one of the leading gas transporters. (The annual transport volume is more than 90 billion cubic meters.) Among our main objectives is by means of real-time systems to compensate frequent steep changes in gas delivery from Ukraine (former Soviet Union) to be a reliable and stabilizing member of the global gas transport system. Well-known west and east European producers developed the cores of the applied software systems. Firstly, there was a standard quickly computing non-stationary system. It was useful when we needed to compute some missing SCADA measurements and filter faulty ones. After addition of missing sensors and doubling of pressure sensors the requirements were changed. Comparison of calculation results with SCADA database and experimental real-time measurements showed that it would be beneficial to further expand accuracy in transient environment as well as to include algorithms for transient optimization. The recently installed software for transient optimization so far has not been implemented for the whole system. Although it is really accurate with deviation around 3 % from real data, calculations are rather time consuming in viewpoint of dispatcher. Therefore, currently the software is used just for the highly accurate non-stationary nonisothermal forecast of SPP-DSTG pipeline system behavior. Another really important application of this software is numerical analysis of processes in branched pipeline section. It deserves a special focus because corroded pipelines frequently cross inhabited areas. By highly accurate real-time gas leak detection and localization the software will decrease potential harmful influence on inhabitants and environment. Section 1. Description of simulation object Typical gas transportation facility combines some gas compressor stations (CS), connected with each other by multiline linear segments of main gas pipelines (LSMP) consisting of some parallel-laid pipes (lines) with big diameter [3]. Length of LSMP between adjoining CS can change from some tens to hundreds kilometers. Working pressure equals to 4,5÷8,0 MPa as a rule. LSMP is laid underground, on the ground, aboveground or in water (at passages through the water barriers). CS consists of one or some compressor shops (CSh). A group of gas compressor units (GCU) is installed in compressor shop. These GCU are equipped with centrifugal supercharger. Connection of GCU in compressor shops and connection of compressor shops between each other is realized with the help of single-line high pressure pipeline system. These pipelines are called as the technological gas pipelines (TP). As a rule the length of TP doesn't exceed one - two thousands meters. Dust catchers are used at CS for treating of natural gas (incoming in centrifugal supercharger) from solid and liquid impurity elements; air-cooling apparatus (ACA) are used at CS for natural gas cooling.

1.0 ABSTRACT As natural gas pipeline operations within North America become more competitive, most companies are looking for any advantage to reduce annual operating and maintenance expenses which will keep transportation tolls as low as possible. With the major advances in pipeline SCADA systems and significant improvements in desktop computing, Real Time Models (RTM's) have become a reality in the natural gas pipeline industry over the past decade. RTM's have typically been implemented on pipelines to take the place of physical field facilities that are required to provide pipeline pressure data where SCADA information has been too difficult to obtain or justify. This has been a common occurrence in recent years as new residential communities move in on existing pipeline rights of way. When new pipelines are constructed, the ability to integrate SCADA facilities is much easier since the additional costs can be absorbed into the larger overall project cost. Once a pipeline is utilizing and applying SCADA data, an RTM can be implemented and ultimately become a multi-functional tool for gas controllers and engineering support staff to operate and optimize the pipeline. One of the primary challenges for pipeline companies employing an RTM is endeavoring to keep the model current with system network modifications as well as changes in company personnel. Moreover, an RTM is quite often developed with no intention of being implemented as a mission critical system, which in turn can cause the greatest degeneration of the intended application. This lack of recognition inevitably results in disuse and disinterest. Without this importance given to the RTM a large majority of them realize the fate of ending up locked in a back room collecting dust. A typical response from a company employee asked if they still use their RTM is "the person who developed it transferred to a different department" or "the network is so far out of date". Realistically, when an RTM is operationally distinguished as a mission critical system and is integrally linked to a pipeline SCADA system, the results can be very rewarding for employees responsible for maximizing the optimal performance of the pipeline. This paper will recount the methodology of how Alliance Pipeline installed a mission critical RTM model and how it is currently being used nearly two years later. The model was designed to perform many tasks and calculations that most other pipelines would house within their SCADA systems. Alliance resolved that the RTM software was incomparable, with regard specifically to hydraulic calculations. Therefore, the RTM is treated and supported with a similar level of criticality, as is the pipeline SCADA system.

ABSTRACT Operation of the Huldra field commenced on November 2001. It is a gas condensate field, which has been developed with a not normally manned wellhead platform remotely controlled from the existing, manned Veslefrikk B platform. A first stage separation process is installed at the platform to separate gas and liquid. Two pipelines emanate from the Huldra field - a 93.2-mile [150 Km] 20" inner diameter pipeline transporting wet gas from Huldra to the Heimdal platform and an 8" inner diameter 9.9-mile [16 Km] pipeline transporting unstabilised condensate, including water, to the Veslefrikk platform. Due to the hydrocarbon mixture, the flow through these pipelines exhibits multiphase behaviour and therefore requires a multiphase real-time simulation model for surveillance and optimised control. Statoil was responsible for development of the Huldra field and is the field operator. The transient multiphase code OLGA has been an important tool in all phases of the project from the decision to develop the field and into the production phase. The design of the Huldra wet gas pipeline was a significant improvement in multiphase flow transport technology due to the long large diameter pipeline which should be tied-in to the existing Heimdal platform with restricted liquid processing capacity. For the condensate line efficient and good environmental hydrate and wax control methods are selected. This paper describes the requirements of the simulation engine and the pipeline modelling system. This leads to a clear split between the functionality that is necessarily encapsulated in the simulation engine and the functionality that can be incorporated within the wider On-Line System environment developed by Energy Solution International for gas pipeline modelling. The aim is to provide a common level of functionality throughout the system. Functions for multiphase flow pipelines, such as: model tuning, leak detection, liquid accumulation, and composition tracking need to be considered as well. A brief description of the approach to these issues is given. The strategy for operating the pipeline and its impact on extending the functionality of the existing OLS system is presented. This paper gives a brief description of the initial operational experiences with the realtime model. Page 2 of 30 1 Introduction In November 2001, the Huldra field commenced production. Design and start-up of the transport system for wet gas and condensate from Huldra is an extension of current experience. Statoil, as the operator of the Huldra field, awarded Gassco contracts for operational support for the condensate and wet gas pipelines. Valuable experience related to operational aspects and real-time modelling of large-scale multiphase flow systems has been gained after start-up of production. Huldra is a gas/condensate field located in the North Sea at a water depth of 410 ft [125 meters]. After a first stage separation the rich gas containing water and MEG is routed 93.2 miles [150 km] to the Heimdal platform for further processing.

The Caspian Pipeline Consortium (CPC) combines the cooperative efforts of the governments of the Russian Federation, the Republic of Kazakhstan, the Sultanate of Oman and a group of international oil companies including Chevron, Mobil and Lukarko. It represents one of Russia's largest-ever industrial development ventures, spanning over 1,600 km from the rich Tengiz oil fields in Western Kazakhstan, to those along the Caspian Sea and on to the Black Sea coast in Russia, with an eventual capacity of 1.34 million barrels per day. The pipeline runs from Tengiz (Kazakhstan) to Novorossyisk (Russia) with 5 pump stations and over 100 mainline block valves. The primary mission for pipeline design and control was to provide the basis for an efficient, safe and environmentally sound operation. Environmental protection being a key concern for this project, construction would adhere to the most stringent standards of the European Union, the World Bank and other international organizations. To meet these standards, the simulation model that would eventually be used to control and operate the pipeline was also used in the design phase for engineering analysis and optimization. The system needed to include comprehensive SCADA with fully integrated pipeline simulation, leak detection and the ability to perform predictive and look-ahead modeling of the pipeline. Applications also include Threshold Setting, Maximum Throughput Calculations Pipeline Inventory Management, Scraper Tracking, Accounting, Quality Bank, Off-line Planning and Forecasting and Operator Training and Certification. Industrial-quality reliability and redundancy was required for all critical communications, leak detection, control locations and servers. INTRODUCTION On July 11, 2002, the Caspian Pipeline Consortium (CPC) reached the target of six million tons of crude oil delivered to world markets through its pipeline system from the Tengiz oil field in Kazakhstan to the Marine Terminal near Novorossiisk. The six millionth ton of crude oil was loaded on the 11th onto the tanker "Katja" - the 60th tanker since loading of the first tanker, the "Minerva Alexandra", started the comprehensive testing phase of CPC-Russia's Marine Terminal on October 13, 2001. The "Katja" was being loaded simultaneously with another tanker at total loading velocity 20,500 tons per hours, indicating that the Marine Terminal had reached its full project capacity. ChevronTexaco chartered both tankers - the shipper is Tengizchevroil. In other developments, in late June CPC-Russia obtained its operating license from the Russian Federation Ministry of Transportation to conduct all loading-unloading activities at CPC's Marine Terminal. The license, renewable every five years, was granted without any limitations. Earlier, on June 14, 2002, the State Acceptance Commission signed the Act of Acceptance of the CPC Marine Terminal, which verified that all requirements for construction, safety and environmental protection had been met successfully.